The present invention relates to routing calls through a communications network, and in particular to an improved neural network solution for routing calls through a three stage interconnection network.
A neural network is a parallel, distributed, data processing system. A neural network contains a large number of processing elements or neurons of simple processing capability, the number of neurons being the size of the network. The neurons are connected with each other to form a fully connected, or nearly fully connected network. In general, the network performs parallel data processing based on a constraint satisfaction paradigm that has been shown to lead to collective computation capabilities. A neural network solution refers to a specific neural network architecture and set of interconnection weights that result in a neural network capable of solving a specific problem.
The problem of routing a call through a three stage interconnection network requires the choice of an appropriate route through the interconnection network. Since the problem potentially entails an exhaustive search of all possible paths through the interconnection network, it is a good candidate for the use of a neural network. Others have previously proposed neural network solutions to handle routing problems in communications networks. However, none of such solutions have shown guaranteed convergence to a correct answer and the parameters selected for the neural networks either have not been identified or have been based on trial and error. Also, the prior solutions have required an excessive number of neurons and some of them have disadvantageously allowed circular routes through the communication or interconnection network. In addition, the prior solutions have not provided for preferential call placement, i.e., for the preferential use of certain center sections of an interconnection network when routing calls through the network.